Yusof, Yuhanis and Mustaffa, Zuriani (2016) A review on optimization of least squares support vector machine for time series forecasting. International Journal of Artificial Intelligence & Applications, 7 (2). pp. 35-49. ISSN 0976-2191

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Abstract

Support Vector Machine has appeared as an active study in machine learning community and extensively used in various fields including in prediction, pattern recognition and many more. However, the Least Squares Support Vector Machine which is a variant of Support Vector Machine offers better solution strategy. In order to utilize the LSSVM capability in data mining task such as prediction, there is a need to optimize its hyper parameters. This paper presents a review on techniques used to optimize the parameters based on two main classes; Evolutionary Computation and Cross Validation.

Item Type:	Article
Uncontrolled Keywords:	Least Squares Support Vector Machine, Evolutionary Computation, Cross Validation, Swarm Intelligence
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	School of Computing
Depositing User:	Dr. Yuhanis Yusof
Date Deposited:	28 Jun 2016 02:16
Last Modified:	09 Aug 2016 07:59
URI:	https://repo.uum.edu.my/id/eprint/18308

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